Web Reference: Jun 11, 2025 · torch.func, previously known as “functorch”, is JAX-like composable function transforms for PyTorch. This library is currently in beta. What this means is that the features generally work (unless otherwise documented) and we (the PyTorch team) are committed to bringing this library forward. Jul 3, 2024 · The advanced autodiff tutorial explains how to compute Jacobians via a composition of vmap and vjp. Without looking at the source code for jacfwd or torch.autograd.functional.jacobian, write a function to compute the Jacobian using forward-mode AD and a for-loop. We will walk through usecases where torch.func improves the use of PyTorch APIs. Common examples include computing per-sample-gradients, vectorizing functions and creating ensemble of models.
YouTube Excerpt: Speaker: Shagun Sodhani, Tech Lead, Meta Abstract: This talk will focus on using
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